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Sensors Webinar | Sensor Centric-Data Intense Approaches to Manufacturing Operations from Cradle to Grave

22 Sep 2023, 16:00 (CEST)

Diagnostics, Machine Monitoring, Prognostics, Preventative and Productive Maintenance, Condition-Based Maintenance, Fault Diagnosis
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Welcome from the Chairs

10th Sensors Webinar

Sensor Centric-Data Intense Approaches to Manufacturing Operations from Cradle to Grave

We are delighted to welcome you to participate in the webinar, entitled "Sensor-Centric Data-Intense Approaches to Manufacturing Operations from Cradle to Grave." The webinar will address various concepts, from developing and deploying smart sensors in your operations, to securely transferring the data generated from those sensors to the cloud for further analysis. Finally, we will introduce a world expert, who will discuss how the latest advancements in artificial intelligence (AI) and machine learning (ML), can be used to process the substantial amounts of data that your next-generation facility generates. These discussions will link the life of your data from creation/cradle to final cloud processing/grave. Furthermore, these same data might be critical for maintenance, process control, and warranty information, meaning the life of your manufacturing data extends well beyond the initial production cycle. We will wrap up with an engaging discussion about the benefits of sensor-centric data-intense manufacturing operations (and some opportunities that will necessitate pursuing them), and we will highlight and address some of the pitfalls and threats that may accompany this digital transformation.

Date: 22 September 2023

Time: 4:00 pm CEST | 10:00 am EDT | 10:00 pm CST Asia

Webinar ID: 878 8150 0308

Webinar Secretariat: journal.webinar@mdpi.com

Event Chairs

Department of Mechanical Engineering, George Mason University, Fairfax, USA

DETAILS
Bio
Janis Terpenny is Program Director of the Manufacturing Systems Integration (MSI) program at the National Science Foundation (NSF). She is also a Professor with joint appointments in the Systems Engineering and Operations Research and Mechanical Engineering departments at George Mason University, USA. Her research interests include smart integrated systems and processes used in design and manufacturing, as well as engineering education. Prior to starting her current jobs, she served in many systems-related academic roles, having been Professor of Industrial and Systems Engineering and Dean of Engineering at the University of Tennessee, Head of the Industrial and Manufacturing Engineering Department at Pennsylvania State University, Chair of the Industrial and Manufacturing Systems Engineering Department at Iowa State University, Technology Thrust Lead at the Digital Manufacturing and Design Innovation Institute (DMDII, now MxD), Director of the NSF Center for e-Design, Program Director at NSF in the Division of Undergraduate Education, and a Professor at Virginia Tech and the University of Massachusetts. Terpenny also possesses significant industrial work experience, having completed a 2-year rotational management program at the General Electric Company. She is also a Fellow and Member of ASME and IISE, as well as a Member of AAAS, Alpha Pi Mu, ASEE, INFORMS, SME, and Tau Beta Pi. She is Area Editor of the Engineering Economist, Associate Editor of Computers in Industry, Chair of the ASME Intelligent Manufacturing Technology Group (IMTG), and Senior Vice President for Academics on the IISE Board of Trustees and the ASME Board of Governors.

George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, USA

DETAILS
Bio
Thomas Kurfess is Chief Manufacturing Officer, HUSCO/Ramirez Distinguished Chair in Fluid Power and Motion Control, and a Professor of Mechanical Engineering at the Georgia Institute of Technology, as well as Executive Director at the Georgia Tech Manufacturing Institute. He also serves as Chief Technology Officer at the National Center for Manufacturing Sciences. Kurfess received his SB, SM, and PhD degrees in mechanical engineering from the Massachusetts Institute of Technology (MIT) in 1986, 1987, and 1989, respectively. He also received an SM degree in electrical engineering and computer science from MIT in 1988. From 2019-2021, he took leave to serve as Chief Manufacturing Officer at the Oak Ridge National Laboratory (ORNL), where he was responsible for strategic planning related to advanced manufacturing. He is also a Founding Director for the Manufacturing Science Division at ORNL. During 2012-2013, he served as Assistant Director for Advanced Manufacturing at the Office of Science and Technology Policy in the Executive Office of the President of the United States of America, where he was responsible for coordinating federal-level advanced manufacturing R&D. He currently serves as President of the American Society of Mechanical Engineers, and served as President of the Society of Manufacturing Engineers in 2018. His research interests include the design and development of advanced manufacturing systems targeting secure digital manufacturing, additive and subtractive processes, and large-scale production enterprises. He is an elected member of the National Academy of Engineering and a Fellow of ASME, AAAS, and SME.

Georgia Institute of Technology, Atlanta, USA

DETAILS
Bio
Kyle Saleeby was formerly a research staff member at Oak Ridge National Laboratory in the Manufacturing Science Division. His work focuses on connecting machines and manufacturing processes with Industry 4.0 and Industrial IoT technologies. His current interests center on applications of data analytics and closed-loop control for Hybrid Manufacturing processes, where additive and subtractive (machining) processes are combined within a single machine tool.

Keynote Speakers

Electrical and Electronics Systems Research (EESR) Division, Oak Ridge National Laboratory, Oak Ridge, USA

DETAILS
Bio
Vincent Paquit is Section Head for Secure and Digital Manufacturing in the Manufacturing Science Division and Data Analytics Lead for the Manufacturing Demonstration Facility (MDF) at the Oak Ridge National Laboratory. Paquit joined ORNL in 2004 as a Research Assistant while studying for a PhD in Electrical Engineering at the University of Burgundy, France. His early research interests revolved around computer vision and image processing, such as 2D and 3D image segmentation, pattern recognition, remote sensing data interpretation, machine learning, multi- and hyper-spectral imaging, and algorithm development for GPU platforms. In recent years, he has taken on a leadership role in the development of the Data Analytics Framework for Advanced Manufacturing. This framework enhances the comprehension of manufacturing processes, enabling part qualification and certification, as well as process control and correction. Paquit's team actively contributed to the transformation of the MDF into a digital factory. This transformation involved capturing and analyzing digital threads associated with varied manufacturing technologies employed at the facility, spanning from design and modeling to simulation, material feedstock, and component fabrication and evaluation. Paquit's vision and leadership significantly influenced numerous projects and programs within ORNL, the DOE, and the DoD. With the support of the DOE Advanced Materials and Manufacturing Technologies Office (AMMTO), his work has made a substantial impact in terms of advancing scientific knowledge and innovation in the field of digital manufacturing.

Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden

DETAILS
Bio
Lihui Wang is a Chair–Professor at the KTH Royal Institute of Technology, Sweden. His research interests include cyber–physical production systems, human–robot collaborative assembly, brain robotics, and adaptive manufacturing systems. Professor Wang has several current roles related to these interests. He is Editor-in-Chief of International Journal of Manufacturing Research, Journal of Manufacturing Systems, and Robotics and Computer-Integrated Manufacturing. He has published 10 books and authored more than 650 scientific publications. Professor Wang is also a Fellow of the Canadian Academy of Engineering (CAE), the International Academy for Production Engineering (CIRP), the Society of Manufacturing Engineers (SME), and the American Society of Mechanical Engineers (ASME). He has registered Professional Engineer status in Canada, and he formerly served as President (2020-2021) of the North American Manufacturing Research Institution of SME and Chairman (2018-2020) of the Swedish Production Academy. In 2020, he was selected as one of the 20 Most Influential Professors in Smart Manufacturing by the Society of Manufacturing Engineers.

Department of Systems Engineering and Operations Research, George Mason University, Fairfax, USA

DETAILS
Bio
Paulo Costa is Interim Chair of the Department of Cyber Security Engineering and Director of the C4I and Cyber Center at George Mason University, as well as Vice President for Securing Automation and Supply Chain Security at the DOE's Cybersecurity Manufacturing Innovation Institute (CyManII). His research interests include cyber security, decision support systems, systems design and integration, multi-sensor data fusion, and probabilistic representation and reasoning. Costa has actively participated in various initiatives in the fields of cyber security of mission-critical systems, such as developing algorithms and methodologies to improve the safety and security of railways, airways, and healthcare systems. His most recent project in this field considered advanced manufacturing and supply chain security, in which he devised and coordinated multidisciplinary research teams at CyManII to develop the Cybersecurity Emissions and Energy Quantification framework (CEEQ). As Director of one of oldest and largest research centers at George Mason University, he manages multidisciplinary teams working on advanced research on mission-critical applications at different levels of security. Costa is also a former fighter pilot and has an extensive academic service record, including two tenures as President of the International Society of Information Fusion, where he currently serves as a Member of the Board of Directors.

Webinar Content

In this section, you will find the recordings of this webinar to watch, re-watch and share with your colleagues!

Thank you for your interest in this webinar, entitled "Sensor-Centric Data-Intense Approaches to Manufacturing Operations from Cradle to Grave", which was held on September 22, 2023. The webinar brought together visionary researchers and thought leaders to address key challenges and opportunities for the advancement and adoption of smart manufacturing. The latest advances in artificial intelligence (AI), machine learning (ML), data analytics, and the role of sensing/sensors were discussed in the context of human brain–robot collaboration, methods for determining the return on investment (ROI) for cyber-secure manufacturing, and the control of manufacturing processes as well as quality. Discussions embraced strategies for dealing with substantial amounts of data from next-generation facilities, cradle to grave, including maintenance, process control, and warranty information, well beyond the initial production cycle. The webinar concludes with an engaging discussion about the benefits of sensor-centric data-intense manufacturing operations, as well as highlights that address some of the pitfalls and threats that accompany digital transformation.

Program

Speaker/Presentation

Time in EDT

Time in CEST

Time in CST Asia

Janis Terpenny

Introduction of topic and speakers

10:00-10:10 am

4:00-4:10 pm

10:00-10:10 pm

Lihu Wang

Brain Robotics for Human-Centric Collaborative Assembly

10:10-10:35 am

4:10-4:35 pm

10:10-10:35 pm

Paulo Cesar Costa

How to assess the ROI of introducing new sensors and technologies to advanced manufacturing systems and their associated supply chain

10:35-11:00 am

4:30-5:00 pm

10:35-11:00 pm

Vincent Paquit

How artificial intelligence and machine learning (AI/ML) can be utilized to perform great data analytics. This will be discussed in the context of metal additive manufacturing (AM) and microstructure control on e-beam powder bed systems. Discussion will include how this works and some shortcomings, etc.

11:00-11:25 am

5:00-5:25 pm

11:00-11:25 pm

Q&A Session

Moderated by Thomas Kurfess and Kyle Saleeby

11:25 am-12:00 pm

5:25-6:00 pm

11:25-12:00 pm

Janis Terpenny

Closing of Webinar

12:00 pm

6:00 pm

12:00 pm

Relevant Special Issues

"Sensors for Machine Condition Monitoring, Diagnostics, Prognostics, and Maintenance"

Edited by Janis Terpenny, Thomas Kurfess, Vittal Prabhu and Dazhong Wu
Deadline for manuscript submissions: 25 January 2024

Sponsors and Partners

Organizers

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